Data Scientist

> 2 années d'expérience

CDI

Data Scientist

Machine Learning

Make

Python

✨ About Mistral AI ✨

At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

We democratize AI through high-performance, optimized, open-source, and cutting-edge models, products, and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.

We are a dynamic, collaborative team passionate about AI and its potential to transform society.

Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany, and Singapore. We are creative, low-ego, and team-spirited.

Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.

🚀 Role Summary 🚀

We are seeking skilled and motivated Data Scientists to join our team in Paris. You will work at the intersection of product, research, and engineering. You will analyze user behavior, optimize product performance, and design data-driven features that enhance our AI product suite. This role is ideal for someone who thrives in a dynamic environment, enjoys tackling ambiguous problems, and wants to influence our product roadmap directly. The ideal candidate will have a strong background in data analysis, statistical modeling, and machine learning, with a proven track record of delivering high-quality results in a fast-paced environment. If you’re passionate about data, curious about AI, and eager to shape the data science strategy and make an impact, this is the role for you.

💡 What You Will Do 💡

Define key metrics, understand in-depth the performance of our AI products, and identify opportunities for improvement.
Design and analyze experiments (A/B tests, causal inference) to validate hypotheses and guide product decisions.
Design and implement end-to-end data science projects, from data collection and preprocessing to model building, evaluation, and deployment.
Evaluate model performance in training and production, identifying edge cases, and develop frameworks to measure user satisfaction.
Work with engineering to ensure data quality and accessibility for analytics and ML.
Depending on seniority, mentor peers and share best practices in data science and analytics.

🌟 About You 🌟

Must-have:

Minimum of 2 years of industry experience as a Data Scientist.
Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
Proficiency in Python as well as SQL.
Highly technical but with a strong product acumen.
Experience in extracting insights from large and complex data, summarizing findings, and sharing takeaways for product and engineering teams.
Strong statistical intuition and experience with experimental design, causal inference, and machine learning algorithms.
Excellent communication and ability to explain complex technical concepts to non-technical audiences.
Creative, curious, and innovative — you love exploring new ways to use data.
Low-ego and a team player, eager to collaborate across functions.

Nice-to-have:

Familiarity with DBT or similar tools.
We are looking for folks to work on customer-facing products, enterprise products, and with the science team, so experience working on one or more related topics is a plus.

📋 Hiring Process 📋

Intro call with Recruiter (30 min)
Hiring Manager Interview (30 min)
Technical interview - Python + Stats/ML (60 min)
Homework Assignment (5-day prep) + Review Presentation (60 min)
Value talk interview (30 min)
References

📍 Location & Remote 📍

The position is based in our Paris HQ offices, and we encourage going to the office as much as we can (at least 3 days per week) to create bonds and smooth communication. Our remote policy aims to provide flexibility, improve work-life balance, and increase productivity. Each manager can decide the amount of days worked remotely based on autonomy and a specific context (e.g., more flexibility can occur during summer). In any case, employees are expected to maintain regular communication with their teams and be available during core working hours.

🎁 What We Offer 🎁